PubMed Health⌕ Search

Biomedical subjects

Oliver F Lange

Publications and source records attributed to Oliver F Lange.

5 recordsLinked to original sources
PubMed2006

Can principal components yield a dimension reduced description of protein dynamics on long time scales?

The suitability of principal component analysis (PCA) to yield slow collective coordinates for use within a dimension reduced description of conformational motions in proteins is evaluated. Two proteins are considered, T4 lysozyme and crambin. We present a quantitative evaluation of the convergence of conformational coordinates obtained with principal component analysis. Detailed analyses of (>200 ns) molecular dynamics trajectories and crystallographic data suggests that simulations of a few nanoseconds should generally provide a stable and statistically reliable definition of the essential and near constraints subspaces. Moreover, a systematic assessment of the density of states of the dynamics of all principal components showed that for an optimal separation of time scales it is crucial to include also side chain atoms in the PCA.

Algorithms↗
PubMed2006

Flooding in GROMACS: accelerated barrier crossings in molecular dynamics.

The major bottleneck of today's atomistic molecular dynamics (MD) simulations is that because of the enormous computational effort involved, only processes at nanoseconds to microseconds time scales or faster can be studied directly. Unfortunately, apart from a few exceptions, relevant processes, such as chemical reactions or many large scale conformational transitions in proteins, occur at slower time scales and therefore are currently far out of reach for conventional MD. The flooding technique addresses this problem by inclusion of a flooding potential into the force field. This flooding potential locally destabilizes the educt state and thereby significantly accelerates the escape from the initial energy well without affecting the reaction pathway. Here, we summarize the theory and method for the computational chemistry community and detail the implementation within the official version 3.3 of the freely available MD program package GROMACS. Two examples shall demonstrate the application of flooding to accelerate conformational transitions and chemical reactions. The second example was carried out within a QM/MM framework.

Butanes↗
PubMed2006

Collective Langevin dynamics of conformational motions in proteins.

Functionally relevant slow conformational motions of proteins are, at present, in most cases inaccessible to molecular dynamics (MD) simulations. The main reason is that the major part of the computational effort is spend for the accurate description of a huge number of high frequency motions of the protein and the surrounding solvent. The accumulated influence of these fluctuations is crucial for a correct treatment of the conformational dynamics; however, their details can be considered irrelevant for most purposes. To accurately describe long time protein dynamics we here propose a reduced dimension approach, collective Langevin dynamics (CLD), which evolves the dynamics of the system within a small subspace of relevant collective degrees of freedom. The dynamics within the low-dimensional conformational subspace is evolved via a generalized Langevin equation which accounts for memory effects via memory kernels also extracted from short explicit MD simulations. To determine the memory kernel with differing levels of regularization, we propose and evaluate two methods. As a first test, CLD is applied to describe the conformational motion of the peptide neurotensin. A drastic dimension reduction is achieved by considering one single curved conformational coordinate. CLD yielded accurate thermodynamical and dynamical behaviors. In particular, the rate of transitions between two conformational states agreed well with a rate obtained from a 150 ns reference molecular dynamics simulation, despite the fact that the time scale of the transition (approximately 50 ns) was much longer than the 1 ns molecular dynamics simulation from which the memory kernel was extracted.

Biophysics↗
PubMed2006

Generalized correlation for biomolecular dynamics.

Correlated motions in biomolecules are often essential for their function, e.g., allosteric signal transduction or mechanical/thermodynamic energy transport. Because correlated motions in biomolecules remain difficult to access experimentally, molecular dynamics (MD) simulations are particular useful for their analysis. The established method to quantify correlations from MD simulations via calculation of the covariance matrix, however, is restricted to linear correlations and therefore misses part of the correlations in the atomic fluctuations. Herein, we propose a general statistical mechanics approach to detect and quantify any correlated motion from MD trajectories. This generalized correlation measure is contrasted with correlations obtained from covariance matrices for the B1 domain of protein G and T4 lysozyme. The new method successfully quantifies correlations and provides a valuable global overview over the functionally relevant collective motions of lysozyme. In particular, correlated motions of helix 1 together with the two main lobes of lysozyme are detected, which are not seen by the conventional covariance matrix. Overall, the established method misses more than 50% of the correlation. This failure is attributed to both, an interfering and unnecessary dependence on mutual orientations of the atomic fluctuations and, to a lesser extent, attributed to nonlinear correlations. Our generalized correlation measure overcomes these problems and, moreover, allows for an improved understanding of the conformational dynamics by separating linear and nonlinear contributions of the correlation.

Bacteriophage T4↗